Method and apparatus for virtual subtraction of stool from registration and shape based analysis of prone and supine scans of the colon

ABSTRACT

Certain embodiments of the present invention provide a system and method for identifying stool particles in virtual dissection data for a colon. A shape classification may be determined for a segmented colon by three-dimensional filtering of a prone data set and a supine data set. The shape classification may be mapped onto a prone virtual dissection image and a supine virtual dissection image. The prone data set and the supine data set may be registered using one-dimensional registration to determine a registration. Shapes may be localized based on the shape classification and the registration for the prone virtual dissection and the supine virtual dissection. A distance metric may be applied to the localized shapes to identify stool particles. The identified stool particles may be suppressed. A prone virtual dissected image and a supine virtual dissected image may be displayed having the stool particles suppressed.

RELATED APPLICATIONS

This application is a continuation-in-part of the following UnitedStates Patent Application Publication Nos., each of which is herebyincorporated by reference in their entirety: 2005/0094858 (applicationSer. No. 10/698,701) entitled, “Method And Apparatus For SynchronizingCorresponding Landmarks Among A Plurality Of Images”, filed Oct. 31,2003 now U.S. Pat. No. 7,274,811; 2005/0152587 (application Ser. No.10/756,872) entitled, “System And Method For Overlaying Color Cues On AVirtual Representation Of An Anatomical Structure”, filed Jan. 12, 2004;2005/0256399 (application Ser. No. 10/844,073), entitled, “Methods ForSuppression Of Items And Areas Of Interest During Visualization”, filedMay 12, 2004; 2005/0244042 (application Ser. No. 10/709,355) entitled“Filtering And Visualization Of A Multidimensional Volumetric Dataset”,filed Apr. 29, 2004. This application hereby incorporates by referencein its entirety U.S. Pat. No. 6,996,205, entitled, “Methods AndApparatus To Facilitate Review Of CT Colonography Exams”, filed Dec. 22,2003, related to Provisional application No. 60/482,038, filed on Jun.24, 2003.

FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[Not Applicable]

MICROFICHE/COPYRIGHT REFERENCE

[Not Applicable]

This application is a continuation-in-part of the following UnitedStates Patent Application Publication Nos., each of which is herebyincorporated by reference in their entirety: 2005/0094858 (applicationSer. No. 10/698,701) entitled, “Method And Apparatus For SynchronizingCorresponding Landmarks Among A Plurality Of Images”, filed Oct. 31,2003; 2005/0152587 (application Ser. No. 10/756,872) entitled, “SystemAnd Method For Overlaying Color Cues On A Virtual Representation Of AnAnatomical Structure”, filed Jan. 12, 2004; 2005/0256399 (applicationSer. No. 10/844,073), entitled, “Methods For Suppression Of Items AndAreas Of Interest During Visualization”, filed May 12, 2004;2005/0244042 (application Ser. No. 10/709,355) entitled “Filtering AndVisualization Of A Multidimensional Volumetric Dataset”, filed Apr. 29,2004. This application hereby incorporates by reference in its entiretyU.S. Pat. No. 6,996,205, entitled, “Methods And Apparatus To FacilitateReview Of CT Colonography Exams”, filed Dec. 22, 2003, related toProvisional application No. 60/482,038, filed on Jun. 24, 2003.

BACKGROUND OF THE INVENTION

The present invention generally relates to a system and method forautomatic image processing of multiple images of an object. Inparticular, the present invention relates to a system and method forsynchronizing corresponding locations among multiple images of anobject.

Medical diagnostic imaging systems encompass a variety of imagingmodalities, such as x-ray systems, computerized tomography (CT) systems,ultrasound systems, electron beam tomography (EBT) systems, magneticresonance (MR) systems, and the like. Medical diagnostic imaging systemsgenerate images of an object, such as a patient, for example, throughexposure to an energy source, such as x-rays passing through a patient,for example. The generated images may be used for many purposes. Forinstance, internal defects in an object may be detected. Additionally,changes in internal structure or alignment may be determined. Fluid flowwithin an object may also be represented. Furthermore, the image mayshow the presence or absence of objects in an object. The informationgained from medical diagnostic imaging has applications in many fields,including medicine and manufacturing.

One particular application for the information acquired from medicaldiagnostic imaging is in the diagnosis and treatment of cancer. Althoughthere are many different kinds of cancer, they all share a common cause:an uncontrollable growth of abnormal cells. As most cancer cells growand accumulate, they form a tumor. Medical diagnostic imaging allowsvarious sections of the human body to be examined for cancerous cellsand tumors.

A particular type of medical diagnostic imaging used in detectingcancerous growths is tomographic reconstruction. Tomographicreconstruction reconstructs tomographic images for two-dimensional andthree-dimensional image scans. Tomographic reconstruction reconstructsan image from image data projections (such as x-ray projections)generated in an image acquisition system. Data from multiple projectionsare combined to produce an image representing an object. Often,two-dimensional slices are reconstructed from scans of athree-dimensional object. The two-dimensional slices may be combined toconstruct a three-dimensional image. These two or three dimensionalimages may be viewed by a physician, or other health care practitioners,in search of cancerous growths, for example.

However, not all forms of cancerous growths are easily detected usingtomographic reconstruction. One such area is that of colorectal cancer.Excluding skin cancers, colorectal cancer is the third most commoncancer diagnosed in both men and women in the United States. TheAmerican Cancer Society estimates that about 105,500 new cases of coloncancer (49,000 men and 56,500 women) and 42,000 new cases of rectalcancer (23,800 men and 18,200 women) will be diagnosed in 2003.Colorectal cancer is expected to cause about 57,100 deaths (28,300 menand 28,800 women) during 2003.

Colorectal cancers are thought to develop slowly over a period ofseveral years. Most colorectal cancers begin as a polyp, a mass oftissue that grows into the center of the tube that makes up the colon orrectum. Once a cancer forms in these polyps, the cancer may grow intothe center of the colon or rectum. The cancerous polyp will also growinto the wall of the colon or rectum where the cancer cells may growinto blood vessels. From these vessels, the cancer cells may then breakaway, spreading to other parts of the body.

Although colon cancer is the third most common cancer diagnosed and thesecond largest cause of cancer related death in the United States, ithas been estimated that up to ninety percent of colon cancers may beprevented. Colonic polyps develop slowly and may take years beforebecoming cancerous. If polyps are found early, they may be removedbefore they develop into cancer, or if they are already cancerous, theymay be removed before the cancer spreads. Thus, the one of the keys topreventing colon cancer is screening for potential cancerous polyps. Theimportance of screening is further magnified because most colonic polypsdo not produce any symptoms, and nearly seventy-five percent of peoplewho develop colon cancer have no risk factors for the disease, yieldingno warning for the onset of cancer.

The American Cancer Society recommends that every person over the age offifty be screened for colon cancer. They estimate, that if everyone weretested, tens of thousands of lives could be saved each year. However,although colon cancer is the second largest cause of cancer relateddeath, only forty percent of Americans who are at risk for the diseaseare currently screened as recommend. So few individuals are screenedbecause people typically find the screening methods for colon cancerdistasteful. For example, one screening method calls for testing thestool for blood. The blood screening method requires patients to collectstool samples at home to send to the doctor's office for testing.Another screening method, a colonoscopy, involves a bowel cleansingprocess which lasts about a day, followed by sedation and an examinationof the colon with a five-foot-long probe. Due to the time consuming andinvasive nature of a colonoscopy, many people choose not to have thecolonoscopy.

Tomographic reconstruction of a colon has been advocated as a promisingtechnique for providing mass screening for colorectal cancer.Tomographic reconstruction of a colon is often called a computedtomography colonography (CTC), also called a virtual colonoscopy. Avirtual colonoscopy is a technique for detecting colorectal neoplasms byusing a computed tomography (CT) scan of a cleansed and air-distendedcolon. The CTC scan typically involves two CT scans of the colon, aprone scan and a supine scan. A prone scan may include a patient lyingface down, for example. Moreover, a supine scan may include a patientlying face up, for example. Both the prone and supine scans capturehundreds of images of a patient's abdomen forming a prone and supineimage set. Each image is captured in 20-30 seconds, for example, whichtranslates into an easier, more comfortable examination than isavailable with other screening tests. Usually, a CTC takes approximatelyten minutes, and a person may return to work the same day. Thus, asystem and method providing a quick, effective and friendly screeningprocess would be highly desirable. There is a need for a method andsystem that increases early detection of cancerous polyps and othermaterials.

However, currently CTC is not a practical clinical tool for colon cancerscreening. For CTC to be a practical procedure of screening for coloncancers, a technique should reduce the time for interpreting a largenumber of images in a time-effective fashion, and for detecting polypsand masses with high accuracy. Currently, however, interpretation of anentire CTC examination is time consuming. A typical CTC examinationproduces 150-300 axial CT images for each the supine and prone imagesets, yielding a total of 300-700 images/patient. Studies show that acase interpretation time per patient is between 15 and 40 minutes evenwhen the reading is done by experts in abdominal imaging. Thus a systemand method that reduces CTC case interpretation time would be highlydesirable.

In addition, the diagnostic performance of CTC currently remainsvulnerable to perceptual errors. Several studies have reported arelatively low sensitivity, 40%-70%, for example, in the detection ofpolyps using a CTC examination. A low detection rate may result from thesystem and method used to display and view the images. Thus, an improvedsystem and method used to display and view the images may improve thedetection of cancerous growths.

As previously mentioned, a CTC examination involves two scans: a pronescan and a supine scan. Multiple scans may be obtained due to theelastic structure of the colon. That is, the colon is a flexiblestructure, much like an accordion, that changes shape based on bodyposition. Portions of the colon that are visible in a prone view, maynot be visible in a supine view, and vice versa, for example. Thus, inorder to have an accurate representation of the colon, both a prone andsupine scan should be conducted.

Another reason that performing two scans of the colon provides a moreaccurate representation than a single scan is that even though pre-examprocedures call for a bowel cleansing process, excess liquid or residualfecal matter within the colon may still be lingering during the exam.Because the excess material has a tendency to shift between a proneimage set and a supine image set, target items or potential polyps maybe observable in one image set and obscured in the other. Hence, bothimage sets must be compared and contrasted during a CTC caseinterpretation.

Often, both the prone and supine image sets are compared and contrastedsimultaneously. Ideally, a particular portion of the colon in one set issearched for polyps, and then the corresponding portion of the colon inthe second set is also reviewed for polyps. Each potential growth orpolyp is scrutinized to determine whether it actually is a polyp orsimply excess material. One method to distinguish excess material from apolyp is to compare corresponding locations of the colon in both theprone and supine image sets. Because the excess material tends to shiftbetween a prone and supine image scan, the excess material seen in aparticular location in one image set will usually be in a differentlocation in the corresponding image set. However, polyps typically donot change location between the image sets. Thus, if a growth is in aparticular location of the colon in both image sets, the growth may be apotential polyp.

Observing a similar growth in corresponding locations of the colon inboth the prone and supine image sets facilitates a comparison analysis.Current systems and methods for viewing CTC prone and supine image setsdo not link the image sets together. Unlinked images may createdifficulty for a user when determining whether or not correspondinglocations in the prone and supine image sets are being viewed. Hence,the user currently guesses if the portion of the colon being viewed inthe prone image set is the same portion of the colon being viewed in thesupine image set.

Guessing whether the portion of the colon being viewed in the proneimage set is the same portion of the colon being viewed in the supineimage set is very time consuming due to the manual, imprecise nature ofthe analysis. Forcing a user to guess at colon location accounts for anextremely long CTC case interpretation time per patient. A user spends asignificant amount of time ascertaining whether the user is viewingcorresponding locations of the colon in each of the prone and supineviews. Even if a user thinks the user is viewing two correspondinglocations of a colon, currently the user may not be certain. As isexplained above, a long CTC case interpretation time currently makesclinical screening impracticable.

Also, rough estimation of corresponding locations provides for a highlyinaccurate procedure for distinguishing excess material from potentialcancerous growths or other objects. The low detection rate of detectingpolyps using a CTC examination mentioned above is partially caused by auser's inability to determine whether the user is viewing correspondinglocations of the colon in prone and supine views. As is explained above,the low detection rate currently makes clinical CTC screeningimpracticable.

Therefore, a need exists for a system and method which automaticallysynchronizes corresponding locations of an object among multiple images.Such a system and method may be used to synchronize correspondinglocations of prone and supine image sets of a CTC examination, forexample, thereby reducing CTC case interpretation time and increasingdetection rate of potentially cancerous polyps.

SUMMARY OF THE INVENTION

Certain embodiments of the present invention provide a system and methodfor automatically synchronizing corresponding locations of an object andindicators among multiple images. In an embodiment of the invention, theacquired images are converted into one dimensional digital profile maps.Next, a common reference point among the images is identified. Next,various landmarks are then identified in the one dimensional digitalprofile maps. The landmarks are then equated to determine thecorresponding landmarks among the plurality of images, as well as thecorresponding landmarks location from the reference point and thecorresponding landmarks location from each other. Finally, informationregarding the corresponding landmarks and the corresponding landmarksrespective distances is registered.

In an embodiment of the invention, a method involves viewing a pluralityof images with corresponding landmarks and corresponding indicators. Themethod may obtain at least one image of an object for a first image setand at least one image of the object for a second image set. Then,corresponding landmarks are synchronized between the first image set andthe second image set. Next, the method includes displaying a firstindicator at a first location on a first displayed image from the firstimage set. Then, the second image set is searched for a locationcorresponding to the first location in the first image set. Finally, thesecond displayed image of the object from the second image set isdisplayed along with a second indicator corresponding to the firstindicator.

In an embodiment of the invention, a system synchronizes correspondinglandmarks and indicators among a plurality of images of an object. Thesystem comprises a dimensional converter unit for use in creating onedimensional digital profile maps of the images based on two or threedimensional digital representations of the object. The system alsocomprises a reference point identification unit for use in identifying acommon reference point among all the images. Moreover, the systemcomprises a landmark identification unit for use in identifyinglandmarks in the one dimensional digital profile maps. Also, the systemcomprises a correlation unit for use in equating corresponding landmarksamong the images, as well as computing the corresponding landmarksdistances from the reference point and the corresponding landmarksdistances from each other. Finally, the system comprises a registrationunit for use in registering the corresponding landmarks as well as therespective distances among each one dimensional digital profile map.

The method and apparatus of the invention allows a synchronization ofimages of multiple perspectives of the same object using correspondinglandmarks. Synchronization ensures an observer is viewing a same portionof an object, and allows an indicator to identify a particular locationof the same object, even when viewing different perspectives. Forexample, a particular application of an embodiment of the invention maybe used to synchronize corresponding locations and indicators of theprone and supine images of a CTC examination, thereby reducing the CTCcase interpretation time and increasing the detection rate ofpotentially cancerous polyps. Such improvements in CTC examinationcapabilities increase the possibility of using a CTC examination forlarge scale screening for colonic polyps, and other identificationoperations, for example.

Certain embodiments of the present invention include a method forsuppressing stool particles in virtual data for a colon. The method mayinclude accessing a prone data set and a supine data set. The method mayalso include three-dimensional filtering of a prone data set and asupine data set to determine a shape classification for a segmentedcolon. Next, mapping the shape classification onto a prone virtualdissection image and a supine virtual dissection image. The prone dataset and the supine data set may be registered by using one-dimensionalregistration to determine a registration. The shapes may be localizedbased on the shape classification and the registration for the pronevirtual dissection and the supine virtual dissection. A distance metricmay be applied to the localized shapes to identify stool particles. Theidentified stool particles may be suppressed. Finally, a prone virtualdissected image and a supine virtual dissected image may be displayed.

In an embodiment of the present invention, the colon may be prepped.Also, the three-dimensional filtering may be performed using a Curvaturetensor filter. The results of the three-dimensional filtering are adescription of local shape characteristics. The step of localizingshapes may include localizing shapes indicative of anatomical landmarksin the colon. Also, the distance metric may include determining thedistance between the location of a spherical shape in the prone virtualdissection image and the corresponding location of the spherical shapein the supine virtual dissection image with reference to thelocalization. If the distance between the location of a spherical shapein the prone virtual dissection image and the corresponding location ofthe spherical shape in the supine virtual dissection image is greaterthan a predetermined threshold value, classifying the spherical shape asstool.

Certain embodiments of the present invention also include acomputer-readable storage medium including a set of instructions for acomputer. The set of instructions includes an accessing routine foraccessing a prone data set and a supine data set. The set ofinstructions also includes a three-dimensional filtering routine forthree-dimensional filtering of a prone data set and a supine data set todetermine a shape classification for a segmented colon. The set ofinstructions also includes a mapping routine for mapping the shapeclassification onto a prone virtual dissection image and a supinevirtual dissection image. The set of instructions also includes aregistration routine for registering the prone data set and the supinedata set using one-dimensional registration to determine a registration.The set of instructions also includes a localization routine forlocalizing shapes based on the shape classification and the registrationfor the prone virtual dissection and the supine virtual dissection. Thelocalizing routine may include localizing shapes indicative ofanatomical landmarks in the colon. The set of instructions also includesa distance metric routine for applying a distance metric to thelocalized shapes to identify stool particles. The set of instructionsalso includes a suppression routine for suppressing identified stoolparticles. The set of instructions also includes a display routine fordisplaying a prone virtual dissected image and a supine virtualdissected image.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an image processing system for synchronizingcorresponding landmarks among a plurality of images of an object used inaccordance with an embodiment of the present invention.

FIG. 2 shows a graphic representation of data used in accordance with anembodiment of the present invention.

FIG. 3 depicts an explanatory drawing depicting a correspondence oflandmarks among the supine and prone views used in accordance with anembodiment of the present invention.

FIG. 4 illustrates a flow diagram for a method for synchronizingcorresponding landmarks among a plurality of images of an object inaccordance with an embodiment of the present invention.

FIG. 5 illustrates a flow diagram for a method for viewing a pluralityof images with corresponding landmarks used in accordance with anembodiment of the present invention.

FIG. 6 illustrates a supine virtually dissected view of a human colonand a prone virtually dissected view of a human colon.

FIG. 7 illustrates a flow diagram for identifying and subtracting stoolparticles from virtual dissection images of a prone and supine data setin accordance with an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1, illustrates an image processing system 100 used in accordancewith an embodiment of the present invention. The system 100 includes animage source unit 105. The image source unit contains a first image set103 and a second image set 107 (not shown). The system 100 also containsa memory unit 110, a dimension converter unit 115, a reference pointidentification unit 120, a landmark identification unit 125, acorrelation unit 130, a registration unit 135, an operator console 140,an image display unit 145, a display forward mapping unit 150, a displayinverse mapping unit 155, and an image display unit 160.

In an embodiment, the system 100 preprocesses image data 103, 107 andthen makes the processed image data 103, 107 available for display andnavigation by a user. Alternatively, the image data is available fordisplay prior to being processed by the system 100. An image source unit105 provides the image data 103, 107 for processing to the memory unit110. The memory unit 110 stores the image data 103, 107. The memory unit110 communicates with the dimension converter unit 115, the displayforward mapping unit 150, the display inverse mapping unit 155, and theregistration unit 135. Preprocessed image data 103, 107 is communicatedto the dimensional converter unit 115. The dimension converter unit 115performs operations and communicates with the reference pointidentification unit 120. The reference point identification unitperforms operations and communicates with the landmark identificationunit 125. The landmark identification unit performs operations andcommunicates with the correlation unit 130. The correlation unit 130performs operations and communicates with the registration unit 135. Theregistration unit 135 organizes the processed data and communicates withthe memory unit 110. The memory unit 110 then communicates the processedimage data 103, 107 with the display forward mapping unit 150 and thedisplay inverse mapping unit 155. The display forward mapping unit 150communicates with the image display unit 145. The display inversemapping unit 155 communicates with the image display unit 160. Theoperator console unit 140 interacts with the image display unit 145 andthe image display unit 160.

The components of the system 100 may be separate units, may beintegrated in various forms, and may be implemented in hardware and/orin software. Particularly, the dimension converter unit 115, the displayforward mapping unit 150, and the display inverse mapping unit 155 maybe a single unit. Also, multiple image sets may be used. Although FIG. 1exemplifies an embodiment of the invention that uses two images sets, (afirst image set 103 and a second image set 107) the invention itself isnot limited to two image sets. Alternatively, multiple images may betaken from a single image set. Moreover, multiple image display unitsmay be used. Although FIG. 1 exemplifies an embodiment of the inventionthat uses two image display units, the invention itself is not limitedto two image sets.

Referring again to FIG. 1, the first image set 103 and second image set107 may be two images or two collections of images, for example, of thesame object from different views. For instance, the first image set 103may contain one or more images of an object in a first position, and thesecond image set 107 may contain one or more images of an object in asecond position. As an example, the object may be lying on a first side,with a second side facing upward, for a first image set 103, forexample. During the second image set 107, the object may be turned overso the object is lying on the second side, with the first side facingupward, for example.

The individual images within the image sets 103, 107 may contain thesame parameters or different parameters as the other images within theimage set. For explanatory purposes only, the image set may be designedto capture the view of an object as one proceeds around the object in acircular fashion. As an example, an image in the image set may be takenevery one degree as images are captured in a 360 degree circle aroundthe object. In this example, 360 images would exist in the image set.Embodiments of the invention are not limited to circular pattern imagesets, nor are embodiments of the invention limited to one degreeincrements within an image set or the degree unit as a measuring point.An image set is a set of images, regardless of whether the set containsone image, or many images.

Images and image sets may be obtained from a variety of sources andmethods. As an example, images and image sets may be acquired as eithertwo, three, or four dimensional images. Two dimensional images include adual vector plane, three dimensional images include a three vectorplane, and four dimensional images include a three vector plane and atime component. The imaging equipment may be directly connected to thesystem 100 or indirectly connected to the system 100. An example of anindirect connection may be imaging equipment connected to an imagestorage unit, such as a picture archiving and communications system(PACS), which is connected to the system 100 over a data network. Anymethod and apparatus capable of generating or delivering the images andimage sets may be suitable for use with the system 100.

Once acquired by the system 100, the preprocessed first image set 103and preprocessed second image set 107 are transmitted to the memory unit110. The memory unit 110 stores two, three, or four (time) dimensionaldata as provided by the first image set 103 and second image set 107.The stored image sets 103 and 107 may be sent to the display units 145and 160 for display, or transmitted to the dimension converter unit 115.

In an embodiment of the invention, the dimensional converter unit 115 isa forward dimensionality converter unit. The forward dimensionalityconverter unit is used to convert the two, three, or four dimensionalimages of the first image set 103 and the second image set 107 into onedimensional projection profile maps using data projection methods. Thedata projection method is chosen from a list of methods comprising,median projection, maximum projection, and minimum projection. Theprovisional U.S. Patent Application No. 60/482,038 entitled “Methods AndApparatus To Facilitate Review Of CT Colonography Exams,” to inventorsSaad Sirohey, Jerome Knoplioch, Gopal Avinash, Renaud Capolunghi, andLaurent Launay filed on Jun. 24, 2003 is hereby incorporated byreference in its entirety.

Once the dimensional projection profile maps are created for the firstimage set 103 and the second image set 107, the dimensional profile mapsare communicated to the reference point identification unit 120. Thereference point identification unit 120 is used to identify a distinctitem of the object, common to all image sets, that may be used as areference point to base calculations upon. In an embodiment, thereference point is a single item that does not deform or change locationbased upon the object's position.

Alternatively, the first image set 103 and the second image set 107 arecommunicated to the reference point identification unit 120 before thedimension converter unit 115 operates to create one dimensional profilemaps. In an alternative embodiment, the reference point identificationunit 120 identifies a reference point in two, three, or four dimensionalform. Afterward, the reference point identification unit communicateswith the dimension converter unit 115 to create the one dimensionalprofile maps. One dimensional profile maps may also be stored in thememory unit 110.

Referring again to FIG. 1, the one-dimensional projection profile mapsof the first image set 103 and second image set 107 are then transmittedto the landmark identification unit 125. Landmarks are persistentfeatures of an object that may not change based on the position of theobject. The landmark identification unit 125 identifies the persistentfeatures of the object in both the one dimensional projection profilemap of the first image set 103 and the one dimensional projectionprofile map of the second image set 107. For example, the landmarkidentification unit 125 searches the first image set 103 for landmarks.The landmark identification unit 125 locates landmarks A and B, forexample, in the first image set 103. The second image set 107 includesimages of the same object in a different position than in the firstimage set 103. The landmark identification unit 125 locates landmarks Aand B in the second image set 107. That is, landmarks A and B mayrepresent the same structures of the object viewed in different imagesets.

The correlation unit 130 then receives the one dimensional projectionprofile map of the first image set 103, the one dimensional projectionprofile map of the second image set 107, the respective landmarks ineach image set 103, 107 that were identified by the landmarkidentification unit 125, and the reference point. The correlation unit130 compares the landmarks of the first image set 103 with the landmarksof the second image set 107 in search of similar landmarks in each set.As the correlation unit 130 finds similar landmarks, the correlationunit 130 notes a distance of each landmark in each image set from thereference point and a distance between each of the landmarks.

For example, as landmarks A and B in the first image set 103 areidentified by the landmark identification unit 125, the correlation unit130 searches and locates the corresponding landmarks A and B in thesecond image set 107. A distance from the reference point to landmark Ain the first image set 103 and a distance from the reference point tolandmark A in the second image set 107 are noted. Additionally, adistance from the reference point to landmark B in the first image set103 and the distance from a reference point to landmark B in the secondimage set 107, are noted. The correlation unit 130 locates correspondinglandmarks and notes the landmarks respective distances from thereference point. The distance information may also be used to determinedistances between landmarks in an image set. Once the distanceinformation for landmark A and landmark B from the reference point areknown, the distance from landmark A to landmark B may also bedetermined.

The information regarding corresponding landmarks between image sets103, 107 is then transferred to the registration unit 135. Theregistration unit 135 organizes the corresponding landmarks and thelandmark distances from the reference point and from other landmarks.For example, the location of the landmarks A and B in the first imageset 103 is recorded, as well as the distance from landmarks A and B tothe reference point. The distance between landmark A and landmark B inthe first image set 103 is also recorded. Similarly, the location of thelandmarks A and B in the second image set 107 is recorded, as well asthe distance between landmarks A and B and the reference point.Moreover, the distance between landmark A and landmark B in the secondimage set 107 is also recorded.

In an embodiment, the registration unit 135 communicates thecorresponding organization of locations and distances of the respectivelandmarks to the memory unit 110. The memory unit 110 stores thecorresponding organization of landmarks and their respective locationsand distances as one dimensional data.

In an embodiment, once the memory unit 110 has stored the processedimage data 103, 107 as received from the registration unit 135, theprocessed image data 103, 107 is available for display and navigation.As explained above, the image data may be available for display prior toprocessing. For example, images may be displayed on display units 145,160 and be refreshed as image data 103, 107 is processed in the system100. Display of the image data 103, 107 may consist of a whole orpartial two, three, or four dimensional display of the object. Moreover,the number of image sets to be displayed does not control the number ofdisplay units. Any combination of display units and image sets may beused to implement the invention. The combination in FIG. 1 is only anexample.

Navigation of the image data 103, 107 may involve static and/or dynamicimages in two dimensional, three dimensional, and/or four dimensionalviews. The operator console unit 140 may allow a user to set one or moreindicators pointing to a particular location or locations of the imagedisplayed. The indicator may be a marking, such as a cursor, on thedisplay units 145, 160 which serves to point to a particular location ofthe displayed image. The operator console unit 140 may contain a controlmechanism, such as a ball control, keyboard, or mouse, for controllingthe indicator on the display, for example, but any control mechanism maybe used. The operator console unit 140 may also allow a “fly through” ofthe object. During fly through, partial views of the object are viewedin quick succession to create a video of the images within an image set103, 107.

In operation, an operator or program may direct a first image from thefirst image set 103 to be displayed on the image display unit 145 orimage display unit 160. Although FIG. 1 illustrates the operator consoleunit 140 directing only the image display unit 145 to display a firstimage, the operator console unit 140 may also direct image display unit160 to display a first image. However, the display unit 145, 160 chosen,to display a first image from a first image set 103 is referred to asthe dominant display unit. In an embodiment, the dominant display unitcontrols the other subservient display units. The choice of whichdisplay unit 145, 160 is dominant may be altered at any time duringoperation of the system 100.

Referring to FIG. 1, a user or computer program may direct the displayof image set 103 on image display unit 145 and display of image set 107on image display unit 160. In FIG. 1, the example provided demonstratesa situation where the operator has chosen image display unit 145 as thedominant display unit. As such, the operator has control over a firstindicator on image display unit 145 which points to various locations inimage set 103.

An operator may use the first indicator on display unit 145 to point toa location in image set 103. The location of the first indicator is thenforward mapped using the forward mapping unit 150. The forward mappingunit creates a one dimensional projection profile of the location of thefirst indicator in image set 103. The location of the first indicator inimage set 103 is then transmitted to the memory unit 110. Thecorresponding location of the first indicator in image set 107 islocated, along with images in image set 107 pertaining to theindicator's location on the object. A second indicator may then point tothe corresponding location in image set 107. In an embodiment, the firstindicator of image set 103 points to the same location on the object asthe second indicator of image set 107.

The image containing the second indicator and the location of the secondindicator are then passed to the display inverse mapping unit 155. Thedisplay inverse mapping unit 155 is used to convert the one dimensionalprojection profile maps of the chosen image and indicator location intotwo, three, or four dimensional image as requested. The inversedimensionality converter unit 155 further comprises a landmarkelasticity measurement unit (not shown) and a matching unit (not shown).The matching unit uses a circular one-dimensional signal correspondencemethod, such as a maximum correlation measure, a mutual informationmeasure, and a minimum difference measure. The two, three, or fourdimensional image and corresponding indicator acquired from image set107 are then displayed on display unit 160. The image displayed on imagedisplay unit 160 from image set 107 corresponds to the image asdisplayed on image display unit 145 from image set 103. Both displaysallow the user to view the same location of the object in two differentimage sets. Furthermore, the second indicator as displayed in imagedisplay unit 160 points to the same location of the object as the firstindicator in image display unit 145.

A user may change the location of the dominant indicator or portionviewed on the dominant display unit and the subservient display unitsmay display the corresponding location of the indicator and portion ofthe object in the respective image sets.

As an example, the system 100 may be used in conducting a computedtomography colonography (CTC) to detect colon cancer. In a CTC, acomputed tomography (CT) machine is used to acquire images of the humancolon. Two sets of images are acquired, a prone set of images and asupine set of images. A computed tomography machine used to acquire theimages may be a local machine or a machine connected to a network inwhich images may be stored or retrieved. The images are generally two,three, or four dimensional images at acquisition.

FIG. 2 shows a prone and a supine representation of a human colon inaccordance with an embodiment of the present invention. A supine imageset 210 shows a typical three dimensional and a typical two dimensionalrepresentation of a colon from a CT supine scan. A prone image set 220shows a typical three dimensional and a typical two dimensionalrepresentation of a colon from a CT prone scan. The representations arecreated using multiple images in each image set.

Referring again to FIG. 1, the first image set 103 may be referred to asthe supine image set 210 and the second image set 107 may be referred toas the prone image set 220, for example. In an embodiment, the supineimage set 210 and the prone image set 220 are communicated to the memoryunit 110 from the image source unit 105. The memory unit 110 stores thesupine and prone image data 210, 220. The image data 210, 220 istransmitted to the dimension converter unit 115. The dimension converterunit 115 is used to convert the supine image set 210 and the prone imageset 220 from two, three, or four dimensional images into one dimensionalprojection profile maps using data projection methods. The dataprojection method may be chosen from a list of methods comprising,median projection, maximum projection, and minimum projection.

The supine image set 210 and the prone image set 220 are thentransmitted to the reference point identification unit 120. Aspreviously mentioned, the reference point identification unit 120 isused to identify a base point for calculation purposes. In anembodiment, the reference point is a human anus. The anus is ananatomically distinct object that does not substantially deform duringtransitions between prone and supine views. Hence, the location of theanus should be the same in the prone image set 220 as it is in thesupine image set 210, making the location of the anus a usable referencepoint to conduct calculations in both the prone image set 220 and supineimage set 210.

Alternatively, as previously mentioned, the reference pointidentification unit 120 may receive the supine image set 210 and theprone image set 220 as two, three, or four dimensional data. Thereference point identification unit 120 may then find a reference pointbefore the dimension converter unit 115 creates a one dimensionalprojection profile map.

Referring again to FIG. 1, the one dimensional projection profile mapsof the supine image set 210 and the prone image set 220 are thentransmitted to the landmark identification unit 125. As explained above,landmarks are persistent features of an object, regardless of theobject's position. In an embodiment, the landmarks are folds or polypsof the colon, for example. Even though the colon may change positionfrom the prone to supine views, the folds of the colon generally remainrecognizable from the prone to supine views.

FIG. 3 illustrates an example of the landmarks which may be identifiedin accordance with an embodiment of the present invention. The supinetwo dimensional drawing 310 shows landmarks 1, 2, 3, 4, and 5. The pronetwo dimensional drawing 320 shows landmarks 1, 2, 3, 4, and 5. Thereference point 330 is also shown. The landmarks 1, 2, 3, 4, and 5represent various folds of a colon. The reference point 330 representsan anus, for example.

Referring to FIG. 1, once the landmarks in the supine image set 210 andthe prone image set 220 are identified, the image data is transmitted tothe correlation unit 130. The correlation unit 130 identifiescorresponding landmarks between the prone 220 and supine 210 image setsas well as a relative distance from the reference point to the landmarksand distance between the landmarks. For example, referring to FIG. 3,the prone two dimensional drawing 320 contains landmarks 5, 4, 3, 2, and1 and the supine two dimensional drawing 310 contains landmarks 5, 4, 3,2, and 1. The correlation unit identifies that landmark 1 in the pronetwo dimensional drawing 320 is the same structure of the object aslandmark 1 in the supine two dimensional drawing 310. In the example ofthe colon as the object, the correlation unit 130 recognizes that fold 1of the prone two dimensional drawing 320 is the same fold of the colonas fold 1 of the supine two dimensional drawing 310.

The correlation unit 130 then measures a distance between landmark 1 inthe supine two dimensional drawing 310 and the reference point 330.Similarly, a distance from landmark 1 in the prone two dimensionaldrawing to the reference point 330 is noted. Next, the correlation unit130 determines a distance from landmark 1 in the supine two dimensionaldrawing 310 to landmark 2 in the supine two dimensional drawing 310.Similarly, the correlation unit 130 measures a distance from landmark 1in the prone two dimensional drawing 320 to landmark 2 in the prone twodimensional drawing 320. The distance between landmarks is called anintra-landmark distance. The intra-landmark distances in FIG. 3 arereferred to as ds and dp. The correlation unit 130 determines thelocation, distance from the reference point 330, and distance betweenlandmarks, for each pair of corresponding landmarks in both the supineand prone image sets 210, 220.

Pairs of landmarks may be correlated even though the landmarks may notbe located the same distance from the reference point 330 in each imageset. Non-uniform stretching of the colon from the prone and supinepositions is demonstrated in FIG. 3. Even though landmarks 3, 4, and 5of each image set 210, 220 are generally the same structure of the sameobject, landmarks 3, 4, and 5 of the prone set 220 are differentdistances from the reference point 330 than landmarks 3, 4, and 5 of thesupine image set 210. In FIG. 3, a difference between the distance dpand ds highlights non-uniformity of distance. The relationship betweenthe prone and supine image sets is as follows:xs=xp*dp/ds  [Equation 1],

where:

xs=distance in the supine view from the reference point,

xp=distance in the prone view from the reference point,

ds=intra-landmark length of the supine landmarks, and

dp=intra-landmark length of the prone landmarks.

Referring again to FIG. 1, in an embodiment, after the correlation unit130 determines the location of the corresponding landmarks, the distancefrom the reference point and the distance between the landmarks isorganized in the registration unit 135. The organized information in theregistration unit 135 is then transmitted to the memory unit 110. Thememory unit 110 stores the processed data.

In an embodiment, an operator or program may direct an indicator to marka first location of the supine image set 210. The indicator andcorresponding portion of the supine image set 210 is displayed on theimage display unit 145. The location of the selected indicator andportion of the supine image set 210 are then transmitted to the displayforward mapping unit 150. The display forward mapping unit 150 creates aone dimensional projection profile of the selected location. The memoryunit 110 is then searched for the landmarks in the prone image set 220corresponding to the landmarks of the one dimensional projection profileof the supine image set 210. Once the corresponding landmarks in theprone image set 220 are found, the landmarks, the image in which thelandmarks reside, and the location of the indicator are transmitted tothe display inverse mapping unit 155.

The display inverse mapping unit 155 is then used to convert the onedimensional projection profile maps information onto two, three, or fourdimensional images using a landmark elasticity measurement unit and amatching unit. The matching unit uses a circular one-dimensional signalcorrespondence method, such as a maximum correlation measure, a mutualinformation measure, and a minimum difference measure, to match onedimensional data to a two, three, or four dimensional representation.

A second image is then displayed on the image display unit 160 with anindicator corresponding to the location of the indicator on the imagedisplay unit 145. Hence, both the image display unit 145 and the imagedisplay unit 160 display the same portion of the colon. Moreover, theindicator of the display unit 145 points to the same location of thecolon as the indicator of the display unit 160. Alternatively, imagedisplay unit 145 may display the prone view of the colon, and imagedisplay unit 160 may display the supine view of the colon, for example.Alternatively, as mentioned above, both the prone and supine views maybe displayed on a single display unit.

FIG. 4 illustrates a flow diagram for a method 400 for synchronizingcorresponding landmarks among a plurality of images of an object inaccordance with an embodiment of the present invention. First, at step405, at least two sets of images are acquired. Next, at step 410, afirst image set is displayed. Then, at step 415, a one dimensionaldigital profile forward map of the sets of image data is created. Atstep 420, a reference point in each image set is located. Next, at step425, the landmarks in each image set are located. At step 430, thecorresponding landmarks among the image sets are located to determinewhich landmarks in one image set correspond to landmarks in other imagesets. Also at step 430, the respective distances of landmarks from thereference point and the distances between landmarks are calculated. Atstep 435, the corresponding landmarks and distances may be registered.Then, at step 440, the landmarks and distance data are stored in memory.At step 445, the location of a first indicator on a first image isnoted. Next, at step 450, the first indicator is forward mapped tocreate a one dimensional projection profile of the first indicator. Atstep 455, the corresponding location of the first indicator in thesecond image is found. At step 460, the image or image set containingthe corresponding location to the first indicator is inverse mapped tocreate a two, three, or four dimensional image. Finally, at step 465, asecond image is displayed containing a second indicator identifying asame location of an object as the first indicator identifies in thefirst image. Each of these steps is described in more detail below.

In an embodiment, the method 400 may be used to synchronizecorresponding landmarks between a prone and supine computed tomographycolonography (CTC) scan. As previously discussed, in a CTC scan, twosets of images of the human colon, for example, are acquired, a proneset of images and a supine set of images.

At step 405, images are acquired. The first image set may be a supineimage set 210, and the second image set may be a prone image set 220,for example. After the supine image set 210 and the prone image set 220are acquired, at step 410, a first image set is displayed. The firstimage set may be either the supine image set 210 or the prone image set220, for example.

At step 415, the supine 210 and prone 220 image sets are forward mappedfrom two, three, or four dimensional data into one dimensionalprojection profile maps. Representing image data as a one dimensionalprojection profile map allows the data to be processed and landmarks andother image characteristics to be more easily identified. In anembodiment, the supine 210 and prone 220 image sets are forward mappedto convert the two, three, or four dimensional images of the supine 210and the prone 220 image sets into one dimensional projection profilemaps using data projection methods. The data projection method is chosenfrom a list of methods comprising, median projection, maximumprojection, and minimum projection.

After the one dimensional projection profile maps of the supine 210 andprone 220 image sets are created, a reference point 330 in each imageset is located. As previously mentioned, the reference point 330 is usedto identify a base point for calculation purposes. In an embodiment, thereference point 330 is a human anus. The anus is an anatomicallydistinct object that may not deform during transitions between prone andsupine views. Hence, the location of the anus should be the same in theprone image set 220 as it is in the supine image set 210, making thelocation of the anus a usable reference point 330 to conductcalculations in both the prone image set 220 and supine image set 210.

Alternatively, the reference point 330 may be located in the supineimage set 210 and the prone image set 220 as two, three, or fourdimensional data. In this alternative embodiment, the reference point330 among the image sets is located before the data is forward mapped tocreate a one dimensional digital profile. Referring to FIG. 4, in analternative embodiment, step 415 and 420 could be toggled

At step 425, landmarks are located in both the supine and prone imagesets 210, 220. As previously mentioned, landmarks are features of anobject that may not change based on the position of the object.Landmarks may be the folds of the colon, for example. Even though thecolon may change position from the prone to supine views, the folds ofthe colon may not change. The location of the folds in each of thesupine and prone image sets with respect to from the reference point 330may be determined.

At step 430, the landmarks of the prone image set 220 are correlatedwith the landmarks of the supine image set 210 to determinecorresponding landmarks among the image sets. The correlation betweenlandmarks exists even though the landmarks may not be located the samedistance from the reference point in each image set 210, 220. Thedistance of the landmarks from the reference point and the distance ofthe landmarks from each other is then measured. The location, distancefrom the reference point, and distance between landmarks, for each pairof corresponding landmarks in both the prone and supine image sets 210,220 is determined.

At step 435, once the corresponding landmarks and distances are found,the corresponding landmarks and distances are registered, along with theimages in which those landmarks may be found. At step 440, the locationand distances for the registered landmarks may be stored in memory.

At step 445, the location of a first indicator on a first image set isnoted. In an embodiment, the user positions the first indicator on thesupine 210 or prone 220 image set while the user is viewing the supine210 or prone 220 image set. A computer may then note the position of thefirst indicator on the first image set, for example. The location of theindicator may be among a two, three, or four dimensional image set andthe image set may be static or dynamic.

Once the first indicator on the first image set is noted, at step 450,the first indicator is forward mapped to create a one dimensionalprojection profile of the first indicator and the image selected. Theone dimensional projection profile of the first indicator is used instep 455 to find a second indicator on a second image set whichcorresponds to the location of the first indicator on the first imageset. For example, if a user positions the first indicator at aparticular location in the supine image set 210, the correspondinglocation of the first indicator is located within the prone image set220. In an embodiment, the process of matching the location of the firstindicator to the location of the second indicator involves locating thecorresponding landmarks and respective distances among the image sets asdescribed above in steps 405-440.

Once the second indicator corresponding to the first indicator islocated, the images or image set comprising the second indicator isinversed mapped at step 460. The images are inverse mapped from onedimensional projection profile maps into two, three, or four dimensionalimages using a landmark elasticity measurement and a matching method.The matching method may be among comprising the maximum correlationmeasure, the mutual information measure, and minimum difference measure.

Finally at step 465, a second image is displayed with an indicatorcorresponding to the location of the indicator on the first image. Forexample, a supine image set 210 and a prone image set 220 may bothdisplay the same portion of a colon with indicators identifying the samelocation of the colon.

Alternatively, the method 400 may display the same portion of an object,such as a colon, for example, without the indicators. Moreover, the sameportion of the object, such as a colon for example, does not have to bedisplayed. The locations of the object displayed may be different whilethe indicators identify the same location of the object.

The embodiment of the invention described above is not limited to a userdirecting a prone image set 220. The supine image set 210 may also bedirected and the prone image set 220 commanded to automatically displaysimilar landmarks. In an embodiment, a software program may be used todisplay images and identify landmarks.

FIG. 5 illustrates a flow diagram for a method 500 demonstrating amethod for viewing a plurality of images with corresponding landmarks.First, at step 510, two sets of images are obtained. Next, the imagesets are synchronized at step 520. At step 530, a first indicator isdirected to be displayed on a first image. At step 540, a correspondinglocation of the first indicator is located in a second image set.Finally, at step 550, a second image with an indicator corresponding tothe location of the indicator in the first image is displayed. Each ofthese steps will be developed more fully below.

In an embodiment, the method 500 may be used in viewing multiple imageswith corresponding landmarks among a prone and a supine computedtomography colonography (CTC) scan. As previously discussed, in a CTCscan, two sets of images of the human colon are acquired, a prone set ofimages and a supine set of images.

In an embodiment, at step 510, the first image set 103 may be a supineimage set 210 and the second image set 107 may be a prone image set 220.At step 520, once the prone and supine image sets 210, 220 are acquired,the image sets 210, 220 are processed as previously described, in orderto synchronize corresponding landmarks.

At step 530, a user or software program directs a first image from thefirst image set 103 to be displayed. As an example, the first image maybe a portion of the colon as viewed in the supine image set 210. A useror software program may also direct an indicator on the first image toidentify a particular location on the first image. The indicator is thendisplayed on the image.

At step 540, the corresponding image and indicator within the secondimage set 107 is located. For example, if a user positions the firstindicator at a particular location in the supine image set 210, thecorresponding location of the first indicator is located within theprone image set 220. In an embodiment, the process of matching thelocation of the first indicator to the location of the second indicatorinvolves locating the corresponding landmarks and respective distancesamong the image sets.

At set 550, a second image is displayed. The second displayed image haslandmarks and indicators corresponding to landmarks and indicators inthe first displayed image. Hence, the first displayed image and thesecond displayed image should correspond to the same location of thecolon, but as seen from two separate views, a prone view and a supineview, for example. Moreover, the first indicator and second indicatorshould correspond to the same location of the object.

The method 500 may be repeated to view different areas of the colon orother object being imaged. Moreover, the method 500 is not limited toviewing the colon with two image sets. The method 500 may be used toview any number of image sets of any object.

In an embodiment, the registration of prone and supine data sets may beused in conjunction with other data operations to identify and suppressstool particles in virtual dissection images. For example, theregistration of prone and supine data sets may be used in conjunctionwith shape classification operations as described in parent UnitedStates Patent Application Publication No. 2005/0244042 (application Ser.No. 10/709,355) which is hereby incorporated by reference in itsentirety. Additionally, mapping the shape classification operationresults onto a prone and supine virtual dissected space as described inparent United States Patent Application Publication No. 2005/0152587(application Ser. No. 10/756,872) which is hereby incorporated byreference in its entirety, may be used. Moreover, suppressing identifiedstool particles as described in parent United States Patent ApplicationPublication No. 2005/0256399 (application Ser. No. 10/844,073), ishereby incorporated by reference in its entirety, may be used.

FIG. 6 illustrates the difficulties of distinguishing polyps from stoolin prone and supine virtual dissection images. FIG. 6 shows an image 600illustrating a supine virtually dissected view of a human colon 610 anda prone virtually dissected view of a human colon 620. Identified in theimage 600 is a first anatomical reference point T(n) 630, a secondanatomical reference point T(n+1) 640, a stool particle 660, and a polyp650. As illustrated by the image 600, the stool particle 660 and thepolyp 650 have similar shapes. Accordingly, it may be difficult for ahuman user and/or computer program to distinguish a stool particle froma polyp. The difficulty in distinguishing a stool particle from a polypmay cause a high rate of false positives in an effort to diagnose coloncancer.

One property of stool particles that may help a human user and/orcomputer program distinguish a stool particle from a polyp is theability of a stool particle to “move” between a prone scan and a supinescan. For example, a polyp tends to stay in the same location in boththe supine and prone views. A stool particle, in contrast, tends tochange locations between a supine and prone view. For example, in image600, the stool particle 660 in the supine virtual dissection 610 is in adifferent location than the stool particle 660 in the prone virtualdissection 620. The location of the stool particle 660 in both thesupine 610 and prone 620 virtual dissections may be determined bycomparing the stool particle location to anatomical reference pointsT(n) 630 and T(n+1) 640. As is illustrated in the image 600, the stoolparticle 660 has “moved” closer to anatomical reference point T(n) 630when comparing the supine virtual dissection 610 to prone virtualdissection 620. The polyp 650, however, is generally in the samelocation in both the supine 610 and prone 620 virtual dissections. In anembodiment of the invention, if a shape “moves” more than a thresholddistance within the region defined by anatomical reference points T(n)630 and T(n+1) 640, the shape is classified as stool and may be removedfrom the virtual dissection.

FIG. 7 illustrates a flow diagram for a method 700 for identifying andsubtracting stool particles from virtual dissection images of a proneand supine data set in accordance with an embodiment of the presentinvention. At step 705, the data sets for a colon prone scan and a colonsupine scan of a patient are acquired. In an embodiment, the data setsfor the colon prone scan and colon supine scan of a patient are of aprepped, or cleansed colon. At step 710, the prone and supine data setsare three-dimensional filtered to determine a shape classification for asegmented colon. The three-dimensional filtering to determine a shapeclassification may be performed as described in parent United StatesPatent Application Publication no. 2005/0244042 (application Ser. No.10/709,355), which is hereby incorporated by reference in its entirety.At step 715, the results of the shape classification may be mapped ontoa prone virtual dissection image and a supine virtual dissection imageas described in parent United States Patent Application Publication no.2005/0152587 (application Ser. No. 10/756,872) which is herebyincorporated by reference in its entirety. At step 720, the prone dataset and the supine data set may be registered using one-dimensionalregistration as described above and as part of parent United StatesPatent Application Publication no. 2005/0094858 (application Ser. No.10/698,701), which is hereby incorporated by reference in its entirety.

At step 725, the shapes are localized based on the shape classificationand the registration for the prone virtual dissection and the supinevirtual dissection. The shapes may be localized by identifyinganatomical reference points. For example, in image 600, the anatomicalreference point 630 and anatomical reference point 640 are endpoints forthe shapes labeled as polyp 650 and stool 660. In an embodiment,localization of the shapes 650 and 660 identifies the shapes 650 and 660as located between anatomical reference points 630 and 640.

At step 730, a distance metric is applied to the localized shapes toidentify stool particles. The stool particles may be identified bydetermining if the change in location of the localized shapes from thesupine virtual dissection image to the prone virtual dissection image isgreater than a threshold value. For example, in FIG. 6, the stoolparticle 660 changes location with respect to the anatomical referencepoints 630 and 640 when the location of the stool 660 is compared in thesupine virtual dissection image 610 and the prone virtual dissectionimage 620. If the change in location between the virtual dissectionimages 610 and 620 is greater than a threshold value, the particle isclassified as stool. In an embodiment, the threshold value may bedetermined by computing the elastic displacement of the colon between aprone image and a supine image. Particles displaced greater than theelastic displacement of the colon may be considered stool.

At step 735, the identified stool particles are suppressed. Thesuppressing of the identified stool particles may be performed asdescribed in United States Patent Application Publication no.2005/0256399 (application Ser. No. 10/844,073), which is herebyincorporated by reference in its entirety. Finally, at step 740, theprone virtual dissected image and a supine virtual dissected image,having stool particles suppressed, may be displayed.

The system and method described above may be carried out as part of acomputer-readable storage medium including a set of instructions for acomputer. The set of instructions includes an accessing routine foraccessing a prone data set and a supine data set. The set ofinstructions also includes a three-dimensional filtering routine forthree-dimensional filtering of a prone data set and a supine data set todetermine a shape classification for a segmented colon. The set ofinstructions also includes a mapping routine for mapping the shapeclassification onto a prone virtual dissection image and a supinevirtual dissection image. The set of instructions also includes aregistration routine for registering the prone data set and the supinedata set using one-dimensional registration to determine a registration.The set of instructions also includes a localization routine forlocalizing shapes based on the shape classification and the registrationfor the prone virtual dissection and the supine virtual dissection. Thelocalizing routine may include localizing shapes indicative ofanatomical landmarks in the colon. The set of instructions also includesa distance metric routine for applying a distance metric to thelocalized shapes to identify stool particles. The set of instructionsalso includes a suppression routine for suppressing identified stoolparticles. The set of instructions also includes a display routine fordisplaying a prone virtual dissected image and a supine virtualdissected image.

Certain embodiments may be used to view and compare multiple images of avariety of objects. For example, certain embodiments may be used tosynchronize different image views of luggage or a container. Certainembodiments provide a system and method for automatic image processingof multiple images and multiple views of an object. Certain embodimentsof the present invention provide a system and method for synchronizingcorresponding locations among multiple images of an object.

While the invention has been described with reference to certainembodiments, it will be understood by those skilled in the art thatvarious changes may be made and equivalents may be substituted withoutdeparting from the scope of the invention. In addition, manymodifications may be made to adapt a particular situation or material tothe teachings of the invention without departing from its scope.Therefore, it is intended that the invention not be limited to theparticular embodiment disclosed, but that the invention will include allembodiments falling within the scope of the appended claims.

1. A method for identifying stool particles in virtual dissection datafor a colon, said method comprising: three-dimensional filtering of aprone data set and a supine data set to determine a shape classificationfor a segmented colon; mapping said shape classification onto a pronevirtual dissection image and a supine virtual dissection image;registering the prone data set and the supine data set usingone-dimensional registration to determine a registration; localizingshapes based on said shape classification and said registration for theprone virtual dissection and the supine virtual dissection; and applyinga distance metric to said localized shapes to identify stool particles.2. The method of claim 1, wherein the colon is cleansed.
 3. The methodof claim 1, wherein said three-dimensional filtering may be performedusing a Curvature tensor filter.
 4. The method of claim 1, wherein theresults of said three-dimensional filtering are a description of localshape characteristics.
 5. The method of claim 1, said step of localizingshapes includes localizing shapes indicative of anatomical landmarks inthe colon.
 6. The method of claim 5, wherein said distance metricincludes determining the distance between the location of a sphericalshape in the prone virtual dissection image and the correspondinglocation of the spherical shape in the supine virtual dissection imagewith reference to the localization.
 7. The method of claim 6, wherein ifsaid distance between the location of a spherical shape in the pronevirtual dissection image and the corresponding location of the sphericalshape in the supine virtual dissection image is greater than apredetermined threshold value, classifying the spherical shape as stool.8. The method of claim 1, further comprising the step of suppressingidentified stool particles.
 9. The method of claim 1, further comprisingdisplaying a prone virtual dissected image and a supine virtualdissected image, said views having stool particles suppressed.
 10. Amethod for suppressing stool particles in virtual data for a colon, saidmethod comprising: accessing a prone data set and a supine data set;three-dimensional filtering of a prone data set and a supine data set todetermine a shape classification for a segmented colon; mapping saidshape classification onto a prone virtual dissection image and a supinevirtual dissection image; registering the prone data set and the supinedata set using one-dimensional registration to determine a registration;localizing shapes based on said shape classification and saidregistration for the prone virtual dissection and the supine virtualdissection; applying a distance metric to said localized shapes toidentify stool particles; suppressing said identified stool particles;and displaying a prone virtual dissected image and a supine virtualdissected image.
 11. The method of claim 10, wherein the colon iscleansed.
 12. The method of claim 10, wherein said three-dimensionalfiltering may be performed using a Curvature tensor filter.
 13. Themethod of claim 10, wherein the results of said three-dimensionalfiltering are a description of local shape characteristics.
 14. Themethod of claim 10, said step of localizing shapes includes localizingshapes indicative of anatomical landmarks in the colon.
 15. The methodof claim 14, wherein said distance metric includes determining thedistance between the location of a spherical shape in the prone virtualdissection image and the corresponding location of the spherical shapein the supine virtual dissection image with reference to thelocalization.
 16. The method of claim 15, wherein if said distancebetween the location of a spherical shape in the prone virtualdissection image and the corresponding location of the spherical shapein the supine virtual dissection image is greater than a predeterminedthreshold value, classifying the spherical shape as stool.
 17. Acomputer executable program “stored on a computer readable medium” foridentifying stool particles in virtual data for a colon, said programcomprising: a filtering routine for three-dimensional filtering of aprone data set and a supine data set to determine a shape classificationfor a segmented colon; a mapping routine for mapping said shapeclassification onto a prone virtual dissection image and a supinevirtual dissection image; a registering routine registering the pronedata set and the supine data set using one-dimensional registration todetermine a registration; a localizing routine for localizing shapesbased on said shape classification and said registration for the pronevirtual dissection and the supine virtual dissection; and a distancemetric routine for applying a distance metric to said localized shapesto identify stool particles.
 18. The computer program of claim 17,further comprising a suppression routine for suppressing identifiedstool particles.
 19. The computer program of claim 17, furthercomprising a display routine for displaying a prone virtual dissectedimage and a supine virtual dissected image having stool particlessuppressed.
 20. The computer program of claim 17, wherein saidlocalizing routine includes localizing shapes indicative of anatomicallandmarks in the colon.